id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
17,001 | import json
from functools import wraps
from flask import abort, current_app, request
from flask_login import current_user
from controllers.console.workspace.error import AccountNotInitializedError
from services.feature_service import FeatureService
from services.operation_service import OperationService
class Feature... | null |
17,002 | import json
from functools import wraps
from flask import abort, current_app, request
from flask_login import current_user
from controllers.console.workspace.error import AccountNotInitializedError
from services.feature_service import FeatureService
from services.operation_service import OperationService
class Feature... | null |
17,003 | from datetime import datetime
import pytz
from flask_login import current_user
from flask_restful import Resource, marshal_with, reqparse
from flask_restful.inputs import int_range
from sqlalchemy import func, or_
from sqlalchemy.orm import joinedload
from werkzeug.exceptions import NotFound
from controllers.console im... | null |
17,004 | import json
import logging
from datetime import datetime
from flask_login import current_user
from flask_restful import Resource, abort, inputs, marshal_with, reqparse
from werkzeug.exceptions import Forbidden
from constants.languages import demo_model_templates, languages
from constants.model_template import model_tem... | null |
17,005 | from flask_login import current_user
from flask_restful import Resource, marshal_with, reqparse
from werkzeug.exceptions import Forbidden, NotFound
from constants.languages import supported_language
from controllers.console import api
from controllers.console.app import _get_app
from controllers.console.setup import se... | null |
17,006 | import json
import logging
from collections.abc import Generator
from typing import Union
from flask import Response, stream_with_context
from flask_login import current_user
from flask_restful import Resource, fields, marshal_with, reqparse
from flask_restful.inputs import int_range
from werkzeug.exceptions import For... | null |
17,007 | import json
import logging
from collections.abc import Generator
from typing import Union
import flask_login
from flask import Response, stream_with_context
from flask_restful import Resource, reqparse
from werkzeug.exceptions import InternalServerError, NotFound
import services
from controllers.console import api
from... | null |
17,008 | import flask_restful
from flask_login import current_user
from flask_restful import Resource, fields, marshal_with
from werkzeug.exceptions import Forbidden
from extensions.ext_database import db
from libs.helper import TimestampField
from libs.login import login_required
from models.dataset import Dataset
from models.... | null |
17,009 | import flask_restful
from flask import current_app, request
from flask_login import current_user
from flask_restful import Resource, marshal, marshal_with, reqparse
from werkzeug.exceptions import Forbidden, NotFound
import services
from controllers.console import api
from controllers.console.apikey import api_key_fiel... | null |
17,010 | import flask_restful
from flask import current_app, request
from flask_login import current_user
from flask_restful import Resource, marshal, marshal_with, reqparse
from werkzeug.exceptions import Forbidden, NotFound
import services
from controllers.console import api
from controllers.console.apikey import api_key_fiel... | null |
17,011 | from core.generator.llm_generator import LLMGenerator
from events.message_event import message_was_created
from extensions.ext_database import db
class LLMGenerator:
def generate_conversation_name(cls, tenant_id: str, query):
prompt = CONVERSATION_TITLE_PROMPT
if len(query) > 2000:
que... | null |
17,012 | from events.app_event import app_was_deleted
from extensions.ext_database import db
from models.model import InstalledApp
db = SQLAlchemy()
class InstalledApp(db.Model):
__tablename__ = 'installed_apps'
__table_args__ = (
db.PrimaryKeyConstraint('id', name='installed_app_pkey'),
db.Index('inst... | null |
17,013 | from core.entities.application_entities import ApplicationGenerateEntity
from core.entities.provider_entities import QuotaUnit
from events.message_event import message_was_created
from extensions.ext_database import db
from models.provider import Provider, ProviderType
class ApplicationGenerateEntity(BaseModel):
"... | null |
17,014 | import datetime
import logging
import time
import click
from werkzeug.exceptions import NotFound
from core.indexing_runner import DocumentIsPausedException, IndexingRunner
from events.event_handlers.document_index_event import document_index_created
from extensions.ext_database import db
from models.dataset import Docu... | null |
17,015 | from events.app_event import app_was_created
from extensions.ext_database import db
from models.model import InstalledApp
db = SQLAlchemy()
class InstalledApp(db.Model):
__tablename__ = 'installed_apps'
__table_args__ = (
db.PrimaryKeyConstraint('id', name='installed_app_pkey'),
db.Index('inst... | Create an installed app when an app is created. |
17,016 | from events.app_event import app_model_config_was_updated
from extensions.ext_database import db
from models.dataset import AppDatasetJoin
from models.model import AppModelConfig
def get_dataset_ids_from_model_config(app_model_config: AppModelConfig) -> set:
dataset_ids = set()
if not app_model_config:
... | null |
17,017 | from events.document_event import document_was_deleted
from tasks.clean_document_task import clean_document_task
def clean_document_task(document_id: str, dataset_id: str, doc_form: str):
"""
Clean document when document deleted.
:param document_id: document id
:param dataset_id: dataset id
:param ... | null |
17,018 | from datetime import datetime
from core.entities.application_entities import ApplicationGenerateEntity
from events.message_event import message_was_created
from extensions.ext_database import db
from models.provider import Provider
class ApplicationGenerateEntity(BaseModel):
"""
Application Generate Entity.
... | null |
17,019 | from events.dataset_event import dataset_was_deleted
from tasks.clean_dataset_task import clean_dataset_task
def clean_dataset_task(dataset_id: str, tenant_id: str, indexing_technique: str,
index_struct: str, collection_binding_id: str, doc_form: str):
def handle(sender, **kwargs):
dataset ... | null |
17,020 | import os
import dotenv
def get_env(key):
return os.environ.get(key, DEFAULTS.get(key))
def get_bool_env(key):
value = get_env(key)
return value.lower() == 'true' if value is not None else False | null |
17,021 | import os
import dotenv
def get_env(key):
return os.environ.get(key, DEFAULTS.get(key))
def get_cors_allow_origins(env, default):
cors_allow_origins = []
if get_env(env):
for origin in get_env(env).split(','):
cors_allow_origins.append(origin)
else:
cors_allow_origins = [def... | null |
17,022 | import datetime
import logging
import time
import click
from celery import shared_task
from flask import current_app
from core.indexing_runner import DocumentIsPausedException, IndexingRunner
from extensions.ext_database import db
from models.dataset import Dataset, Document
from services.feature_service import Feature... | Async process document :param dataset_id: :param document_ids: Usage: document_indexing_task.delay(dataset_id, document_id) |
17,023 | import logging
import time
import click
from celery import shared_task
from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
from core.rag.models.document import Document
from extensions.ext_database import db
from models.dataset import Dataset, DocumentSegment
from models.dataset import Do... | Async deal dataset from index :param dataset_id: dataset_id :param action: action Usage: deal_dataset_vector_index_task.delay(dataset_id, action) |
17,024 | import logging
import time
import click
from celery import shared_task
from werkzeug.exceptions import NotFound
from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
from extensions.ext_database import db
from extensions.ext_redis import redis_client
from models.dataset import Document, Doc... | Async Remove document from index :param document_id: document id Usage: remove_document_from_index.delay(document_id) |
17,025 | import logging
import time
import click
from celery import shared_task
from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
from extensions.ext_database import db
from extensions.ext_redis import redis_client
from models.dataset import Dataset, Document
class IndexProcessorFactory:
""... | Async Remove segment from index :param segment_id: :param index_node_id: :param dataset_id: :param document_id: Usage: delete_segment_from_index_task.delay(segment_id) |
17,026 | import datetime
import logging
import time
from typing import Optional
import click
from celery import shared_task
from werkzeug.exceptions import NotFound
from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
from core.rag.models.document import Document
from extensions.ext_database import... | Async create segment to index :param segment_id: :param keywords: Usage: create_segment_to_index_task.delay(segment_id) |
17,027 | import datetime
import logging
import time
import click
from celery import shared_task
from werkzeug.exceptions import NotFound
from core.indexing_runner import DocumentIsPausedException, IndexingRunner
from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
from extensions.ext_database impor... | Async update document :param dataset_id: :param document_id: Usage: document_indexing_update_task.delay(dataset_id, document_id) |
17,028 | import datetime
import logging
import time
import click
from celery import shared_task
from werkzeug.exceptions import NotFound
from core.indexing_runner import DocumentIsPausedException, IndexingRunner
from core.rag.extractor.notion_extractor import NotionExtractor
from core.rag.index_processor.index_processor_factory... | Async update document :param dataset_id: :param document_id: Usage: document_indexing_sync_task.delay(dataset_id, document_id) |
17,029 | import logging
import time
import click
from celery import shared_task
from werkzeug.exceptions import NotFound
from core.indexing_runner import DocumentIsPausedException, IndexingRunner
from extensions.ext_database import db
from models.dataset import Document
class IndexingRunner:
def __init__(self):
se... | Async recover document :param dataset_id: :param document_id: Usage: recover_document_indexing_task.delay(dataset_id, document_id) |
17,030 | import datetime
import logging
import time
import click
from celery import shared_task
from werkzeug.exceptions import NotFound
from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
from core.rag.models.document import Document
from extensions.ext_database import db
from extensions.ext_redi... | Async Add document to index :param document_id: Usage: add_document_to_index.delay(document_id) |
17,031 | import logging
import time
import click
from celery import shared_task
from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
from extensions.ext_database import db
from models.dataset import Dataset, Document, DocumentSegment
class IndexProcessorFactory:
"""IndexProcessorInit.
"""
... | Clean document when document deleted. :param document_ids: document ids :param dataset_id: dataset id Usage: clean_notion_document_task.delay(document_ids, dataset_id) |
17,032 | import datetime
import logging
import time
import uuid
from typing import cast
import click
from celery import shared_task
from sqlalchemy import func
from core.indexing_runner import IndexingRunner
from core.model_manager import ModelManager
from core.model_runtime.entities.model_entities import ModelType
from core.mo... | Async batch create segment to index :param job_id: :param content: :param dataset_id: :param document_id: :param tenant_id: :param user_id: Usage: batch_create_segment_to_index_task.delay(segment_id) |
17,033 | import logging
import time
import click
from celery import shared_task
from flask import current_app, render_template
from extensions.ext_mail import mail
mail = Mail()
The provided code snippet includes necessary dependencies for implementing the `send_invite_member_mail_task` function. Write a Python function `def ... | Async Send invite member mail :param language :param to :param token :param inviter_name :param workspace_name Usage: send_invite_member_mail_task.delay(langauge, to, token, inviter_name, workspace_name) |
17,034 | import logging
import time
import click
from celery import shared_task
from werkzeug.exceptions import NotFound
from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
from extensions.ext_database import db
from extensions.ext_redis import redis_client
from models.dataset import DocumentSegme... | Async disable segment from index :param segment_id: Usage: disable_segment_from_index_task.delay(segment_id) |
17,035 | import datetime
import logging
import time
import click
from celery import shared_task
from werkzeug.exceptions import NotFound
from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
from core.rag.models.document import Document
from extensions.ext_database import db
from extensions.ext_redi... | Async enable segment to index :param segment_id: Usage: enable_segment_to_index_task.delay(segment_id) |
17,036 | import logging
import time
import click
from celery import shared_task
from core.rag.datasource.vdb.vector_factory import Vector
from models.dataset import Dataset
from services.dataset_service import DatasetCollectionBindingService
class Vector:
def __init__(self, dataset: Dataset, attributes: list = None):
... | Async delete annotation index task |
17,037 | import logging
import time
import click
from celery import shared_task
from core.rag.datasource.vdb.vector_factory import Vector
from core.rag.models.document import Document
from models.dataset import Dataset
from services.dataset_service import DatasetCollectionBindingService
class Vector:
def __init__(self, dat... | Add annotation to index. :param annotation_id: annotation id :param question: question :param tenant_id: tenant id :param app_id: app id :param collection_binding_id: embedding binding id Usage: clean_dataset_task.delay(dataset_id, tenant_id, indexing_technique, index_struct) |
17,038 | import datetime
import logging
import time
import click
from celery import shared_task
from werkzeug.exceptions import NotFound
from core.rag.datasource.vdb.vector_factory import Vector
from core.rag.models.document import Document
from extensions.ext_database import db
from extensions.ext_redis import redis_client
fro... | Async enable annotation reply task |
17,039 | import logging
import time
import click
from celery import shared_task
from core.rag.datasource.vdb.vector_factory import Vector
from core.rag.models.document import Document
from models.dataset import Dataset
from services.dataset_service import DatasetCollectionBindingService
class Vector:
def __init__(self, dat... | Update annotation to index. :param annotation_id: annotation id :param question: question :param tenant_id: tenant id :param app_id: app id :param collection_binding_id: embedding binding id Usage: clean_dataset_task.delay(dataset_id, tenant_id, indexing_technique, index_struct) |
17,040 | import logging
import time
import click
from celery import shared_task
from werkzeug.exceptions import NotFound
from core.rag.datasource.vdb.vector_factory import Vector
from core.rag.models.document import Document
from extensions.ext_database import db
from extensions.ext_redis import redis_client
from models.dataset... | Add annotation to index. :param job_id: job_id :param content_list: content list :param tenant_id: tenant id :param app_id: app id :param user_id: user_id |
17,041 | import logging
import time
import click
from celery import shared_task
from werkzeug.exceptions import NotFound
from core.rag.datasource.vdb.vector_factory import Vector
from extensions.ext_database import db
from extensions.ext_redis import redis_client
from models.dataset import Dataset
from models.model import App, ... | Async enable annotation reply task |
17,042 | import datetime
import time
import click
from flask import current_app
from werkzeug.exceptions import NotFound
import app
from extensions.ext_database import db
from models.dataset import Embedding
db = SQLAlchemy()
class Embedding(db.Model):
def set_embedding(self, embedding_data: list[float]):
def get_em... | null |
17,043 | import datetime
import time
import click
from flask import current_app
from werkzeug.exceptions import NotFound
import app
from core.rag.index_processor.index_processor_factory import IndexProcessorFactory
from extensions.ext_database import db
from models.dataset import Dataset, DatasetQuery, Document
class IndexProc... | null |
17,044 | import nbformat
from nbformat import v4 as nbf
import ansi2html
import os
import argparse
nb = nbf.new_notebook()
def write_to_notebook():
if args.notebook:
with open(notebook_path, 'w', encoding='utf-8') as f:
nbformat.write(nb, f)
def add_code_cell_to_notebook(code):
code_cell = nbf.new_c... | null |
17,045 | import nbformat
from nbformat import v4 as nbf
import ansi2html
import os
import argparse
nb = nbf.new_notebook()
def write_to_notebook():
if args.notebook:
with open(notebook_path, 'w', encoding='utf-8') as f:
nbformat.write(nb, f)
def add_markdown_to_notebook(content, title=None):
if titl... | null |
17,046 | from response_parser import *
import copy
import json
from tqdm import tqdm
import logging
import argparse
import os
def initialization(state_dict: Dict) -> None:
if not os.path.exists('cache'):
os.mkdir('cache')
if state_dict["bot_backend"] is None:
state_dict["bot_backend"] = BotBackend()
... | null |
17,047 | from response_parser import *
import copy
import json
from tqdm import tqdm
import logging
import argparse
import os
def get_bot_backend(state_dict: Dict) -> BotBackend:
def switch_to_gpt4(state_dict: Dict, whether_switch: bool) -> None:
bot_backend = get_bot_backend(state_dict)
if whether_switch:
bot_... | null |
17,048 | from response_parser import *
import copy
import json
from tqdm import tqdm
import logging
import argparse
import os
def get_bot_backend(state_dict: Dict) -> BotBackend:
return state_dict["bot_backend"]
def add_text(state_dict, history, text):
bot_backend = get_bot_backend(state_dict)
bot_backend.add_text_... | null |
17,049 | from response_parser import *
import copy
import json
from tqdm import tqdm
import logging
import argparse
import os
def get_bot_backend(state_dict: Dict) -> BotBackend:
return state_dict["bot_backend"]
def bot(state_dict, history):
bot_backend = get_bot_backend(state_dict)
while bot_backend.finish_reason ... | null |
17,050 | import json
import copy
import shutil
from jupyter_backend import *
from tools import *
from typing import *
from notebook_serializer import add_markdown_to_notebook, add_code_cell_to_notebook
if not config['API_KEY']:
config['API_KEY'] = os.getenv('OPENAI_API_KEY')
os.unsetenv('OPENAI_API_KEY')
def get_config... | null |
17,051 | import json
import copy
import shutil
from jupyter_backend import *
from tools import *
from typing import *
from notebook_serializer import add_markdown_to_notebook, add_code_cell_to_notebook
def config_openai_api(api_type, api_base, api_version, api_key):
openai.api_type = api_type
openai.api_base = api_base... | null |
17,052 | import openai
import base64
import os
import io
import time
from PIL import Image
from abc import ABCMeta, abstractmethod
def create_vision_chat_completion(vision_model, base64_image, prompt):
try:
response = openai.ChatCompletion.create(
model=vision_model,
messages=[
... | null |
17,053 | import openai
import base64
import os
import io
import time
from PIL import Image
from abc import ABCMeta, abstractmethod
def create_image(prompt):
try:
response = openai.Image.create(
model="dall-e-3",
prompt=prompt,
response_format="b64_json"
)
return re... | null |
17,054 | import openai
import base64
import os
import io
import time
from PIL import Image
from abc import ABCMeta, abstractmethod
class ImageInquireTool(Tool):
def support(self):
return self.config['model']['GPT-4V']['available']
def get_tool_data(self):
return {
"tool_name": "inquire_image"... | null |
17,055 | from bot_backend import *
import base64
import time
import tiktoken
from notebook_serializer import add_code_cell_error_to_notebook, add_image_to_notebook, add_code_cell_output_to_notebook
def get_conversation_slice(conversation, model, encoding_for_which_model, min_output_tokens_count=500):
def chat_completion(bot_ba... | null |
17,056 | from bot_backend import *
import base64
import time
import tiktoken
from notebook_serializer import add_code_cell_error_to_notebook, add_image_to_notebook, add_code_cell_output_to_notebook
def get_image_size(image_path):
with Image.open(image_path) as img:
width, height = img.size
return width, height
... | null |
17,057 | from bot_backend import *
import base64
import time
import tiktoken
from notebook_serializer import add_code_cell_error_to_notebook, add_image_to_notebook, add_code_cell_output_to_notebook
def add_function_response_to_bot_history(hypertext_to_display, history):
if hypertext_to_display is not None:
if histo... | null |
17,058 | from bot_backend import *
import base64
import time
import tiktoken
from notebook_serializer import add_code_cell_error_to_notebook, add_image_to_notebook, add_code_cell_output_to_notebook
The provided code snippet includes necessary dependencies for implementing the `parse_json` function. Write a Python function `def... | GPT may generate non-standard JSON format string, which contains '\n' in string value, leading to error when using `json.loads()`. Here we implement a parser to extract code directly from non-standard JSON string. :return: code string if successfully parsed otherwise None |
17,059 |
def initialization(state_dict: Dict) -> None:
if not os.path.exists('cache'):
os.mkdir('cache')
if state_dict["bot_backend"] is None:
state_dict["bot_backend"] = BotBackend()
if 'OPENAI_API_KEY' in os.environ:
del os.environ['OPENAI_API_KEY'] | null |
17,060 | import gradio as gr
from response_parser import *
def get_bot_backend(state_dict: Dict) -> BotBackend:
return state_dict["bot_backend"]
f __name__ == '__main__':
config = get_config()
with gr.Blocks(theme=gr.themes.Base()) as block:
"""
Reference: https://www.gradio.app/guides/creating-a-cha... | null |
17,061 | import gradio as gr
from response_parser import *
def get_bot_backend(state_dict: Dict) -> BotBackend:
return state_dict["bot_backend"]
f __name__ == '__main__':
config = get_config()
with gr.Blocks(theme=gr.themes.Base()) as block:
"""
Reference: https://www.gradio.app/guides/creating-a-cha... | null |
17,062 | import gradio as gr
from response_parser import *
def get_bot_backend(state_dict: Dict) -> BotBackend:
return state_dict["bot_backend"]
f __name__ == '__main__':
config = get_config()
with gr.Blocks(theme=gr.themes.Base()) as block:
"""
Reference: https://www.gradio.app/guides/creating-a-cha... | null |
17,063 | import gradio as gr
from response_parser import *
def get_bot_backend(state_dict: Dict) -> BotBackend:
f __name__ == '__main__':
config = get_config()
with gr.Blocks(theme=gr.themes.Base()) as block:
"""
Reference: https://www.gradio.app/guides/creating-a-chatbot-fast
"""
# UI co... | null |
17,064 | import gradio as gr
from response_parser import *
def get_bot_backend(state_dict: Dict) -> BotBackend:
return state_dict["bot_backend"]
f __name__ == '__main__':
config = get_config()
with gr.Blocks(theme=gr.themes.Base()) as block:
"""
Reference: https://www.gradio.app/guides/creating-a-cha... | null |
17,065 | import gradio as gr
from response_parser import *
def get_bot_backend(state_dict: Dict) -> BotBackend:
return state_dict["bot_backend"]
f __name__ == '__main__':
config = get_config()
with gr.Blocks(theme=gr.themes.Base()) as block:
"""
Reference: https://www.gradio.app/guides/creating-a-cha... | null |
17,066 |
def restart_ui(history: List) -> Tuple[List, Dict, Dict, Dict, Dict, Dict, Dict]:
history.clear()
return (
history,
gr.Textbox.update(value="", interactive=False),
gr.Button.update(interactive=False),
gr.Button.update(interactive=False),
gr.Button.update(interactive=Fal... | null |
17,067 | import gradio as gr
from response_parser import *
def get_bot_backend(state_dict: Dict) -> BotBackend:
f __name__ == '__main__':
config = get_config()
with gr.Blocks(theme=gr.themes.Base()) as block:
"""
Reference: https://www.gradio.app/guides/creating-a-chatbot-fast
"""
# UI co... | null |
17,068 | import gradio as gr
from response_parser import *
def get_bot_backend(state_dict: Dict) -> BotBackend:
return state_dict["bot_backend"]
def stop_generating(state_dict: Dict) -> None:
bot_backend = get_bot_backend(state_dict)
if bot_backend.code_executing:
bot_backend.send_interrupt_signal()
else... | null |
17,069 | import jupyter_client
import re
def delete_color_control_char(string):
ansi_escape = re.compile(r'(\x9B|\x1B\[)[0-?]*[ -\/]*[@-~]')
return ansi_escape.sub('', string) | null |
17,070 | from functional import *
class ChoiceHandler:
strategies = [
RoleChoiceStrategy, ContentChoiceStrategy, NameFunctionCallChoiceStrategy,
ArgumentsFunctionCallChoiceStrategy, FinishReasonChoiceStrategy
]
def __init__(self, choice):
self.choice = choice
def handle(self, bot_backend:... | :return: history, whether_exit |
17,071 | import argparse
import os
import torch
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer, AutoModelForCausalLM
import logging
from evalplus.data import get_human_eval_plus,get_mbpp_plus, write_jsonl
def generate_one(example, lang, tokenizer, model, name, flags):
if flags.dataset=... | null |
17,072 | import argparse
import os
import torch
from pathlib import Path
from tqdm import tqdm
import logging
from evalplus.data import (get_human_eval_plus,
write_jsonl,
get_human_eval_plus_hash,
get_mbpp_plus,
get_mbpp_plus_hash,
)
from utils import sanitize_solution,check_correctness,get_groundtruth,SUCCESS
... | null |
17,073 | import argparse
import os
import torch
from pathlib import Path
from tqdm import tqdm
import json
from transformers import AutoTokenizer, AutoModelForCausalLM
import logging
from evalplus.data import (get_human_eval_plus,
write_jsonl,
get_human_eval_plus_hash,
get_mbpp_plus,
get_mbpp_plus_hash,
)
from ... | null |
17,074 | import argparse
import os
import torch
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer, AutoModelForCausalLM
import logging
from evalplus.data import (get_human_eval_plus,
write_jsonl,
get_human_eval_plus_hash,
get_mbpp_plus,
get_mbpp_plus_hash,
)
from utils import... | null |
17,075 | import argparse
import os
import torch
from pathlib import Path
from tqdm import tqdm
import json
from transformers import AutoTokenizer, AutoModelForCausalLM
import logging
from evalplus.data import (get_human_eval_plus,
write_jsonl,
get_human_eval_plus_hash,
get_mbpp_plus,
get_mbpp_plus_hash,
)
from ... | null |
17,076 | import os
from evalplus.sanitize import sanitize
from typing import Any, Dict, List, Optional, Tuple, Union
import itertools
import multiprocessing
import time
from multiprocessing import Array, Value
from typing import Any, Dict, List, Tuple, Union
import numpy as np
import pickle
from evalplus.data.utils import CACHE... | null |
17,077 | import os
from evalplus.sanitize import sanitize
from typing import Any, Dict, List, Optional, Tuple, Union
import itertools
import multiprocessing
import time
from multiprocessing import Array, Value
from typing import Any, Dict, List, Tuple, Union
import numpy as np
import pickle
from evalplus.data.utils import CACHE... | null |
17,078 | import json
import os
from abc import ABC, abstractmethod
from typing import List
from warnings import warn
import openai
import torch
from transformers import (
AutoModelForCausalLM,
AutoModelForSeq2SeqLM,
AutoTokenizer,
StoppingCriteria,
StoppingCriteriaList,
)
from vllm import LLM, SamplingParams... | null |
17,079 | import argparse
import os
from os import PathLike
from model import DecoderBase, make_model
from rich.progress import (
BarColumn,
MofNCompleteColumn,
Progress,
TextColumn,
TimeElapsedColumn,
)
def construct_contract_prompt(prompt: str, contract_type: str, contract: str) -> str:
if contract_type... | null |
17,080 | import json
import os
import pathlib
import shutil
from importlib import util
from inspect import getmembers, isfunction
from typing import Tuple
from tempdir import TempDir
from evalplus.data.mbpp import get_mbpp, mbpp_serialize_inputs
GROUNDTRUTH_MBPP_PATH = pathlib.Path(__file__).parent.parent.parent / "groundtruth/... | null |
17,081 | import json
import os
import pathlib
import shutil
from importlib import util
from inspect import getmembers, isfunction
from typing import Tuple
from tempdir import TempDir
from evalplus.data.mbpp import get_mbpp, mbpp_serialize_inputs
GROUNDTRUTH_MBPP_PATH = pathlib.Path(__file__).parent.parent.parent / "groundtruth/... | null |
17,082 | import json
import os
import pathlib
import shutil
from importlib import util
from inspect import getmembers, isfunction
from typing import Tuple
from tempdir import TempDir
from evalplus.data.mbpp import get_mbpp, mbpp_serialize_inputs
def _ret(entry_point) -> str:
def instrument_inputs(code, entry_point, test_code) ... | null |
17,083 | import json
import os
import pathlib
import shutil
from importlib import util
from inspect import getmembers, isfunction
from typing import Tuple
from tempdir import TempDir
from evalplus.data.mbpp import get_mbpp, mbpp_serialize_inputs
def get_atol(task_id: int) -> float:
float_ans_list = [
82,
85... | null |
17,084 | import ast
import inspect
import json
import multiprocessing
import sys
from concurrent.futures import ProcessPoolExecutor, as_completed
from tqdm import tqdm
from evalplus.data.mbpp import (
MBPP_PLUS_VERSION,
get_mbpp,
get_mbpp_plus,
get_mbpp_plus_hash,
)
from evalplus.eval import is_floats
from evalp... | null |
17,085 | import ast
import inspect
import json
import multiprocessing
import sys
from concurrent.futures import ProcessPoolExecutor, as_completed
from tqdm import tqdm
from evalplus.data.mbpp import (
MBPP_PLUS_VERSION,
get_mbpp,
get_mbpp_plus,
get_mbpp_plus_hash,
)
from evalplus.eval import is_floats
from evalp... | null |
17,086 | import os
from tqdm import tqdm
from evalplus.data import (
get_human_eval_plus,
get_mbpp_plus,
load_solutions,
write_directory,
write_jsonl,
)
from evalplus.sanitize import sanitize
def remove_unindented_lines(code, protect_before, execeptions, trim_tails):
lines = code.splitlines()
cut_id... | null |
17,087 | import os
from tqdm import tqdm
from evalplus.data import (
get_human_eval_plus,
get_mbpp_plus,
load_solutions,
write_directory,
write_jsonl,
)
from evalplus.sanitize import sanitize
def to_four_space_indents(old_code):
new_code = ""
for line in old_code.splitlines():
lspace = len(l... | null |
17,088 | import json
import os
from rich.progress import track
from evalplus.data import get_human_eval_plus, get_human_eval_plus_inputs
LLM_HOME_PATH = "/JawTitan/EvalPlus/humaneval"
model_paths = os.listdir(LLM_HOME_PATH)
cover_info = {f"HumanEval_{i}": {} for i in range(164)}
def get_cover_info():
for model_path in trac... | null |
17,089 |
def fix(data):
# fix 140 https://github.com/evalplus/evalplus/issues/3
assert data[140]["task_id"] == "HumanEval/140"
data[140]["canonical_solution"] = data[140]["canonical_solution"].replace(
"range(len(text)-1, 2, -1)", "range(len(text), 2, -1)"
)
# fix 75 https://github.com/evalplus/ev... | null |
17,090 | import json
import os
import pathlib
from importlib import import_module
from inspect import getsource
from typing import Tuple
from tempdir import TempDir
from evalplus.data.humaneval import get_human_eval
def _ret(entry_point) -> str:
"""This is a hacky function to return some garbages so that we can
successf... | null |
17,091 | import json
import os
import pathlib
from importlib import import_module
from inspect import getsource
from typing import Tuple
from tempdir import TempDir
from evalplus.data.humaneval import get_human_eval
def get_contract_and_ref(task_id: int, entry_point) -> Tuple[str, str]:
mod = import_module(f"groundtruth.hu... | null |
17,092 | import json
import os
import pathlib
from importlib import import_module
from inspect import getsource
from typing import Tuple
from tempdir import TempDir
from evalplus.data.humaneval import get_human_eval
def get_atol(task_id: int) -> float:
if task_id == 2 or task_id == 4:
return 1e-6
elif task_id =... | null |
17,093 | def check_id(data, task_id):
assert data[task_id]["task_id"] == f"HumanEval/{task_id}"
def fix(data):
# fix 53 https://github.com/evalplus/evalplus/issues/8
check_id(data, 53)
data[53]["contract"] = (
'\n assert isinstance(x, int), "invalid inputs" # $_CONTRACT_$'
+ '\n assert isi... | null |
17,094 | import math
def fix(data):
# https://github.com/evalplus/evalplus/issues/29
check_id(data, 35)
data[35]["contract"] += ' assert len(l) != 0, "invalid inputs" # $_CONTRACT_$\n'
# https://github.com/evalplus/evalplus/issues/28
check_id(data, 2)
data[2][
"contract"
] += ' assert n... | null |
17,095 | import math
def check_id(data, task_id):
assert data[task_id]["task_id"] == f"HumanEval/{task_id}"
def check_valid(xs):
if not (isinstance(xs, list) and len(xs) > 0 and len(xs) % 2 == 0):
return False
if not all(type(x) == int for x in xs):
return False
dxs = [xs[i] * i for i in range(1,... | null |
17,096 | import math
def check_id(data, task_id):
assert data[task_id]["task_id"] == f"HumanEval/{task_id}"
def check_valid(s: str):
cnt = 0
for ch in s:
if ch == "(":
cnt += 1
elif ch == ")":
cnt -= 1
else:
return False
if cnt < 0:
retu... | null |
17,097 | import math
def fix(data):
# https://github.com/evalplus/evalplus/issues/44
check_id(data, 115)
data[115]["prompt"] = "import math\n" + data[115]["prompt"].replace(
" import math\n", ""
)
check_id(data, 114)
data[114]["prompt"] = data[114]["prompt"].replace("import math\n", "")
# ... | null |
17,098 | import math
def check_id(data, task_id):
assert data[task_id]["task_id"] == f"HumanEval/{task_id}"
def check_valid(op, num):
try:
exp = ""
for i in range(len(op)):
exp += str(num[i]) + str(op[i])
exp += str(num[-1])
exp = str(eval(exp))
except:
return Fals... | null |
17,099 | import ast
import inspect
import json
import multiprocessing
import sys
from concurrent.futures import ProcessPoolExecutor, as_completed
from tqdm import tqdm
from evalplus.data.humaneval import (
HUMANEVAL_PLUS_VERSION,
get_human_eval_plus,
get_human_eval_plus_hash,
)
from evalplus.eval import is_floats
fr... | null |
17,100 | import ast
import inspect
import json
import multiprocessing
import sys
from concurrent.futures import ProcessPoolExecutor, as_completed
from tqdm import tqdm
from evalplus.data.humaneval import (
HUMANEVAL_PLUS_VERSION,
get_human_eval_plus,
get_human_eval_plus_hash,
)
from evalplus.eval import is_floats
fr... | null |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.